C4.5: programs for machine learning
C4.5: programs for machine learning
Syntactic features and word similarity for supervised metonymy resolution
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Metonymy resolution as a classification task
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
SemEval-2007 task 08: metonymy resolution at SemEval-2007
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
DS'06 Proceedings of the 9th international conference on Discovery Science
Web-Based Lemmatisation of Named Entities
TSD '08 Proceedings of the 11th international conference on Text, Speech and Dialogue
Automatic interpretation of loosely encoded input
Artificial Intelligence
Combining collocations, lexical and encyclopedic knowledge for metonymy resolution
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Local and global context for supervised and unsupervised metonymy resolution
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
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Though the GYDER system has achieved the highest accuracy scores for the metonymy resolution shared task at SemEval-2007 in all six subtasks, we don't consider the results (72.80% accuracy for org, 84.36% for loc) particularly impressive, and argue that metonymy resolution needs more features.